[updated May 17, 2018]
The software, analytics, and digital oilfield landscape has changed in the past few years and I’ve been blessed to be a part of it.
In 2010-2011, we were undertaking the 24-7 operations center. At that time, our vision was teams of operations engineers manually monitoring up to 4 active operations. We knew that value existed but the extraction of value was the unknown. The field operations did not need Big Brother but optimization and problem avoidance were low-hanging fruits. I know we were in the right spot because 3 different solutions providers told me that our company “was leading the land-based innovation in the United States.” That felt good.
I’ve witnessed an evolution over the next several years. Companies no longer considered whether to embrace 24-7 operations centers; today they consider and field operations to be invalid without the support. To be fair, not all E&P companies create their own facilities; many contract with suppliers (typically rig contractors). With this migration to ubiquitous operations centers, advancements in the capabilities were necessarily forthcoming. The industry moved from data, information, and knowledge into understanding – understanding as manifested through predictive analytics, after-event analytics, and variations such as case-based reasoning.
Recently (2015-present), prescriptive analytics, wide-area reservoir analogs, data mining, data science and machine learning are becoming the normal and serious E&P operations mandate these activities.
Digital Transformation is a new buzzword. But is very descriptive of the next step in evolution of the digital oilfield. “Digital transformation is the change associated with the application of digital technology in all aspects of human society. The transformation stage means that digital usages inherently enable new types of innovation and creativity in a particular domain, rather than simply enhance and support traditional methods.“(1)
George Westerman, principal research scientist with the MIT Sloan Initiative on the Digital Economy, is one of those who knows digital transformation when he sees it. “Digital transformation is when companies use technology to radically change the performance or reach of an enterprise,” says Westerman. The drivers tend to be disruption from market newcomers or innovation from rivals seizing the opportunity to win new customers. (2)
Digital Transformation vs Disruption
Digital Transformation is not, and cannot be, all about disruption. Disruption is chaotic and does not produce determined results. Transformation is the evolution of a process of thought. Transformation may be thought of as continuous improvement, but continuous improvement unencumbered by preexisting expectations. I’ve heard it said that continuous improvement of the candle never created the light bulb. But I submit that the light bulb did, in fact, result from the transformation of the candle into the next, logical step.
Digital Transformation is outside of the box application of evolution to good solid engineering principals. The transformation of sensors into end-point IIoT (Industrial Internet of Things) devices; the transformation of after-event forensics into pre-event assessment; the transformation of real-time look-behind into real-time look-ahead.
Why Digital Transformation Matters
Digital Transformation is a survival issue. Experienced digital emigrants (engineers and operations that know the subject intrinsically and have had to learn to embrace ubiquitous computers) are retiring and a phenomenal rate and are being replaced by a class of digital natives (those that simply expect mobility and pervasive computers and automation) who expect data to be available, processed, and providing answers before the question is asked.
According to Lumina Datamatics, “Every organization will have to embrace digital transformation at some level to remain competitive. There can be many manifestations of digital transformation, including using ubiquitous, real-time data and algorithms to processes flexible and autonomous workers. Modern processes and technologies help reduce operational overhead, enabling businesses to invest less in maintenance and more in innovation that supports rapid change.”(3)
Digital Transformation Framework
(4) Enterprise Project states “Although digital transformation will vary widely based on organizations’ specific challenges and demands, there are a few constants and common themes among existing case studies and published frameworks that all business and technology leaders should consider as they embark on digital transformation.
“For instance, these digital transformation elements are often cited:
- Customer experience
- Operational agility
- Culture and leadership
- Workforce enablement
- Digital technology integration”
Moving Digital Transformation Forward
Digital Transformation requires mandate from the top of the company hierarchy. Peter Dahlstrom, et. al. identify 7 crucial decisions which must come from the Executive Leadership Team and the Digital Transformation Team:
Decision 1: Where the business should go
Decision 2: Who will lead the effort
Decision 3: How to ‘sell’ the vision to key stakeholders
Decision 4: Where to position the firm within the digital ecosystem
Decision 5: How to decide during the transformation
Decision 6: How to allocate funds rapidly and dynamically
Decision 7: What to do when
Digital Transformation is here. Digital Transformation is the natural next step. Digital Transformation is not optional.
The Executive Leadership Team must set the tone and the mandate; the operations must embrace the mandate; and the Digital Transformation Engineer must be given charge. (More on the characteristics of the Digital Transformation Engineer later)
(1) Digital transformation – Wikipedia
(2) What is digital transformation? A necessary disruption
(3) Why Digital Transformation Matters
(4) What is digital transformation?
(5) The seven decisions that matter in a digital transformation: A CEO’s guide to reinvention
Peter Dahlström, Driek Desmet, and Marc Singer